[mlpack] Hello Everyone

[Marcus Edel]

Hello Vivek,

>> Yes, I'll look through the list to gain some insights. I also noticed
>> that there's one open PR (#831) with major changes for ANN module
>> lined up. Since, it looks like it will be merged soon can you comment
>> on this year's focus for the deep learning modules idea after this PR
>> is finally merged or will it remain same as last year's of
>> implementing RBM, DBN etc.?
> 
> I'm not the mentor for the deep learning code so I can't say much there,
> but I know that Marcus has merged it in the past few days.  I think when
> the ideas page gets updated over the next week or two, there will be a
> lot more information on the goals this year for the types of projects we
> are interested in.

I'm the one who came up with the 'Essential Deep Learning Modules' project idea.
The focus of the Essential Deep Learning Modules' project will slightly shift
and will be concentrated on more recent ideas. It doesn't mean an implementation
of e.g Deep Belief Networks or Radial Basis Function Networks isn't welcome, we
will definitely look over the code if someone opens a PR. As Ryan already said
we will update the ideas page over the next week or two and add a bunch of
interesting information.

Thanks,
Marcus


> On 30 Jan 2017, at 19:47, Ryan Curtin <ryan at ratml.org> wrote:
> 
> On Wed, Jan 25, 2017 at 11:23:20PM +0530, Vivek Pal wrote:
>>> I'm still willing to mentor the CF idea.  If you search the mailing list
>>> archives, I seem to remember there being a lot of discussion about the
>>> idea last year, and maybe you can find some insights there.
>> 
>> It's great that CF idea is still open. I will certainly look into the
>> list archives to gather some useful information regarding the project.
>> If I'm not wrong this idea was not one of the selected project last
>> year, so I think it'd be worth finding out what was lacking. May be
>> you want to add some input on that?
> 
> We got very many good proposals last year (in total we received over
> 100!) and we had only 6 slots.  If I remember right, the CF code did not
> receive too many proposals.  It's possible that last year, there was
> simply more interest in other projects from both the mentor and the
> student side.
> 
> I'll be going through the Ideas List soon and try and think of good
> projects for improving the CF code.
> 
>>> In the end, anything that helps the CF code get easier to use or
>>> more functional so that users can easily build a recommendation
>>> system would be a great project.
>> 
>> Will the focus be on making existing CF code more functional this year
>> as compared to last year's focus on implementing alternatives to k-NN
>> based CF?
> 
> I'm not picky---both could be good projects.  Or even a project that
> factored in both ideas could be good also.  In the end, if I mentor a
> project on the CF code, I am looking for a clear proposal that will have
> a tangible benefit.  This could take the form of improvements to the
> existing code or adding new approaches for collaborative filtering.
> 
>>> I also remember a lot of discussion about the deep learning modules
>>> project; I'm sure you can find a lot about that one in the archives too.
>> 
>> Yes, I'll look through the list to gain some insights. I also noticed
>> that there's one open PR (#831) with major changes for ANN module
>> lined up. Since, it looks like it will be merged soon can you comment
>> on this year's focus for the deep learning modules idea after this PR
>> is finally merged or will it remain same as last year's of
>> implementing RBM, DBN etc.?
> 
> I'm not the mentor for the deep learning code so I can't say much there,
> but I know that Marcus has merged it in the past few days.  I think when
> the ideas page gets updated over the next week or two, there will be a
> lot more information on the goals this year for the types of projects we
> are interested in.
> 
> But, also, keep in mind that you are always welcome to propose your own
> project idea!  I have seen some great proposals along those lines, where
> the student has identified a problem (or something lacking inside
> mlpack) and then developed a proposal that addresses that problem.
> Yannis' project last year on LSH tuning is a great example of this type
> of approach.
> 
> I hope this is helpful---let me know if I can clarify anything.
> 
> Thanks,
> 
> Ryan
> 
> -- 
> Ryan Curtin    | "Happy premise #2: There is no giant foot trying
> ryan at ratml.org | to squash me." - Kit Ramsey
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